Abstract

In the last years, minimally invasive surgery techniques found their way into the operating theater.
One very promising application is endovascular stent grafting for aortic aneurysms or dissections.
At present, the three-dimensional CTA (Computed Tomography Angiography) model is only used for
preoperative planning but is not available during operation. This
situation is unsatisfactory for CTA provides by far more anatomical
information than the two-dimensional intraoperative fluoroscopic
images taken by a C-arm. Our goal is to close this gap by a Computer Aided Navigation and Planning Tool (CANP).
CTA data is to be visualized intuitively for planning the correct position of the stent and its properties.
During operation itself, CTA serves as basis for augmentation with intraoperative data acquired by the C-arm.
By this means, we hope that radiation exposure for both, surgeon and patient, as well as usage of contrast agent, can be reduced.
This thesis deals with mathematical challenges arising in this context.
Before three-dimensional CTA and two-dimensional fluoroscopic images can be merged in one model, the two modalities have to
be registered. For this purpose, the perspective geometry of the C-arm was determined by a calibration.
Artificial X-ray images computed from CTA, so-called DRRs (Digitally Reconstructed Radiographs) are then to be
overlaid with intraoperative radiographs. An efficient volume rendering technique based on 3D texture-mapping is proposed
for this computationally expensive task. The pose of the CTA model is altered within a virtual C-arm setup by rigid
transformations (rotations and translations). When DRR and radiograph coincide, the patient is registered to his CTA model and
information can be exchanged between both modalities. Iterative best neighbor optimization techniques for an automatic
registration procedure were evaluated. The similarity between DRR and radiograph is estimated by pattern intensity and gradient
difference quality measures. This combination yields promising registration results in affordable time, though differences
between both modalities, especially the influence of contrast agent and other instruments, have to be decreased
in the future in order to achieve a really robust registration.
Furthermore, different direct and indirect volume rendering techniques were evaluated with respect to their suitability for
a fast as well as intuitive visualization of the augmented model.

More Information

In the last years, minimally invasive surgery techniques found their way into the operating theater. One very promising application is endovascular stent grafting for aortic aneurysms or dissections. At present, the three-dimensional CTA (Computed Tomography Angiography) model is only used for preoperative planning but is not available during operation. This situation is unsatisfactory for CTA provides by far more anatomical information than the two-dimensional intraoperative fluoroscopic images taken by a C-arm. Our goal is to close this gap by a Computer Aided Navigation and Planning Tool (CANP). CTA data is to be visualized intuitively for planning the correct position of the stent and its properties. During operation itself, CTA serves as basis for augmentation with intraoperative data acquired by the C-arm. By this means, we hope that radiation exposure for both, surgeon and patient, as well as usage of contrast agent, can be reduced. This thesis deals with mathematical challenges arising in this context. Before three-dimensional CTA and two-dimensional fluoroscopic images can be merged in one model, the two modalities have to be registered. For this purpose, the perspective geometry of the C-arm was determined by a calibration. Artificial X-ray images computed from CTA, so-called DRRs (Digitally Reconstructed Radiographs) are then to be overlaid with intraoperative radiographs. An efficient volume rendering technique based on 3D texture-mapping is proposed for this computationally expensive task. The pose of the CTA model is altered within a virtual C-arm setup by rigid transformations (rotations and translations). When DRR and radiograph coincide, the patient is registered to his CTA model and information can be exchanged between both modalities. Iterative best neighbor optimization techniques for an automatic registration procedure were evaluated. The similarity between DRR and radiograph is estimated by pattern intensity and gradient difference quality measures. This combination yields promising registration results in affordable time, though differences between both modalities, especially the influence of contrast agent and other instruments, have to be decreased in the future in order to achieve a really robust registration. Furthermore, different direct and indirect volume rendering techniques were evaluated with respect to their suitability for a fast as well as intuitive visualization of the augmented model.